The proposed study seeks to develop the first task-dynamic model of sign movement in American Sign Language (ASL). The model will be derived from analyses of kinematic sign production data. Our approach is grounded in the theory of Articulatory Phonology, which proposes that the basic units of speech are articulatory gestures. These gestures are movement tasks that are invariant from one production to another, and their temporal overlap determines the structure of language output. In this study, we hypothesize that articulatory gestures are also the structural primitives of sign, and we seek to discover what the gestures are and how they are timed. During sign production, the articulators must move from one sign's location to the next sign's location, and they must also produce movements that are internal to an individual sign. Theories of sign phonology have tried to differentiate these two types of movement (sign-internal and transitional) from one another and also to determine whether movement is a specified part of the sign, or simply a means of getting from one physical location to another. This study will examine the kinematics and the dynamics of sign-internal and transitional movements in ASL. Kinematic data will be collected from native signers as they produce signs with movements toward or away from specific locations on the body. Signing speed, sign context, and phrase context will be manipulated in order to identify what aspects of sign production remain invariant when movement trajectories and velocities are explicitly varied. Measures derived from the kinematic data will be used as input to a computational model, which will allow us to examine the articulatory gestures. The gestures that are identified from the computational model will then be compared to human production data via an animation program and judged for intelligibility and naturalness by native ASL signers. In this way, we will use converging lines of evidence to test what the minimal units of sign production are and how they are related to each other. PUBLIC HEALTH RELEVANCE This study is relevant to NIH's public health mission, because it contributes to our understanding of the structure of American Sign Language, which is used by an estimated 500,000 people in North America. The study has the potential to enhance the quality of life for Deaf sign language users. Our approach could lead the way toward a more naturalistic means of communication for Deaf people via automated communication systems. If the structure we have proposed accurately describes the minimal units of sign structure, then it should provide the most natural model for sign synthesis.